Smith + Nephew

Smith & Nephew Orthopaedics Ag

Smith Nephew Asia Pacific Pte. Limited

Tnacity Blue Ocean LLC

Anderson, Katherine S.

Nadzadi, Mark Ellsworth

Wilkinson, Zachary Christopher

Scifert, Christopher F.

Mckinnon, Brian W.

Laster, Scott Kennedy

Sharp, Jeffrey A.

Scott Kennedy Laster

Brian William McKinnon

Zachary Christopher Wilkinson

Michael D Ries

Luke Andrew Gibson

Nathaniel Milton Lenz

David Timothy Mehl

Steven B Haas

Mark Ellsworth Nadzadi

David C Kelman

Jeffrey Andrew Sharp

Christopher F Scifert

Katherine S Anderson

Stuart Raymond Morris-Hipkins

Branislav Jaramaz

Sied William Janna

Daniel Farley

Roger Ryan Dees, Jr

Shawn P Mcguan

Brian D Childress

Brian William Mckinnon

Brian W Mc Kinnon

Jr Roger Ryan Dees

Methods, non-transitory computer readable media, and surgical computing devices are illustrated that improve surgical planning using machine learning. With this technology, a machine learning model is trained based on historical case log data sets associated with patients that have undergone a surgical procedure. The machine learning model is applied to current patient data for a current patient to generate a predictor equation. The current patient data comprises anatomy data for an anatomy of the current patient. The predictor equation is optimized to generate a size, position, and orientation of an implant, and resections required to achieve the position and orientation of the implant with respect to the anatomy of the current patient, as part of a surgical plan for the current patient. The machine learning model is updated based on the current patient data and current outcome.

Methods for improved surgical planning using machine learning and devices thereof

A computing system having at least one sensor, at least one processor, and at least one memory including a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the computing system to receive one or more surgical parameters associated with a ligament balancing of a patient's joint, receive real-time sensor data generated by the at least one sensor and indicative of at least one characteristic of the patient's joint, and apply machine learning to determine a next ligament balancing step of the ligament balancing of the patient's joint based on the one or more surgical parameters and the real-time sensor data, wherein the next ligament balancing step is a step of one or more steps intended to result in a target state of the patient's joint identified by the machine learning.

Technologies for intra-operative ligament balancing using machine learning

A system () and device () for mounting and tracking a tracker array during a surgical procedure are described. For example, the system includes a surgical navigation system () including a position tracking system () configured to track one or more tracker arrays, and a device () for mounting a tracker array () onto a patient during the surgical procedure. The device includes an intramedullary (IM) canal component () configured to be inserted into an IM canal () within a bone (). The device further includes a tracker pin () configured to penetrate at least a portion of the bone and engage an inserted end () of the IM canal component, and a tracker array () affixed to the tracker pin. The IM canal component is configured to engage the IM canal of the bone to stabilize the tracker array during the surgical procedure.

Surgical navigation system support array

Systems and methods for determining a care plan for a patient are disclosed. Data from a one or more databases are received or retrieved and used to determine a preferred care plan used to perform a surgical procedure or otherwise treat a patient. The data may include data pertaining to a patient, a healthcare professional, a healthcare facility, an implant, economic data, simulation data, imaging data, and/or the like. The data may be used to determine a plan that provides a positive outcome and patient satisfaction. The data may be updated over time or in real time to improve or refine the determination of care plans for the current patient or other patients.

Methods and systems for providing an episode of care

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing implants for surgical procedures. In some implementations, a model that has been trained using data indicating characteristics of other patients and items used in surgeries for the other patients is obtained. Using the model and patient characteristics for a patient, such as the height and weight of the patient, the items needed for a surgery for a particular patient can be identified. For example, the likelihoods that different sizes of an implant component will be needed can be identified and used to determine which sizes of components should be provided at a medical facility and in the operating room for the patient's surgery.

Providing implants for surgical procedures

Further system and methods associated there with can use a combination of big data, machine learning, and/or regression equations to make living care paths based on sensitivities, probability, and/or statistics, which increases the chances of a living care path being successful. System, in some embodiments, can also provide a visual representation of the treatment options and statistics to the patient and HCP. As configured, system can empower patients, making them more informed about their condition, expectations of recovery, and more confident in their HCP's recommended treatment measure.

Intelligent medical care path systems and methods

A patient-matched cutting block including a surface or point contact features adapted to at least partially conform to or reference a patient specific anatomy. The cutting block having guide slots configured for guiding the movement of cutting tools relative to the patient specific anatomy or features configured to mate to and guide standard cutting guides relative to patient specific anatomy in order to form plateau and eminence resections of the patient specific anatomy.

Patient-matched instrumentation and methods

Methods and apparatus for performing knee arthroplasty, including, but not limited to, bicruciate retaining knee arthroplasty, ore described herein. Methods and apparatus for preparing a distal femur for a femoral implant as well as methods and apparatus for preparing a proximal tibia for a tibial implant are described. These methods and apparatus, in at least some embodiments and uses, facilitate decreasing the complexity of knee arthroplasty procedures such as bicruciate retaining procedures, while maintaining, if not improving on, the safety, accuracy and/or effectiveness of such procedures.

Methods and apparatus for performing knee arthroplasty

A tibial insert includes a base and a post extending from the base along a longitudinal axis. The post has a medial surface, a lateral surface, a height along the longitudinal axis, and a rotational offset in a superior-inferior aspect of the post. The medial surface has a medial section, and the lateral surface has a lateral section oriented substantially parallel to the medial section. The medial section and the lateral section each have a width in a substantially anterior-posterior direction that is sufficient to enable varus/valgus constraint over a flexion/extension range from extension to about 90 to 120 degrees of flexion when the tibial insert is mated with a femoral component.

Knee prosthesis

A tibial insert includes a base and a post extending from the base along a longitudinal axis. The post has a medial surface, a lateral surface, and a height along the longitudinal axis. The medial surface has a medial section, and the lateral surface has a lateral section oriented substantially parallel to the medial section. The medial section and the lateral section each have a width in a substantially anterior-posterior direction that is sufficient to enable varus/valgus constraint over a flexion/extension range from extension to about 90 to 120 degrees of flexion when the tibial insert is mated with a femoral component. The tibial insert further configured such that the medial bearing surface extends further in an inferior direction than the lateral bearing surface and a bottom point of the medial bearing surface is disposed closer to an anterior end portion of the medial bearing surface than a posterior end portion of the medial bearing surface.

Growing community of inventors

Memphis, TN, United States of America

Scott Kennedy Laster